Generation-scheduling-coupled battery sizing of stand-alone hybrid power systems

Ce Shang, Dipti Srinivasan and Thomas Reindl

Energy, 2016, vol. 114, issue C, 671-682

Abstract: Properly sizing the battery energy storage system (BESS) of a stand-alone hybrid power system is an important step to guarantee its reliability and low cost. This study applies the technique of storage-integrated generation scheduling using metaheuristics to the BESS sizing, which helps to achieve the optimal scheduling scheme for each sizing plan, as its advantage over the rule-based sizing method. Such technique incorporates the storage dispatch with the scheduling of the dispatchable generators, and is formulated and solved as an optimisation with metaheuristics. Compared with existing approaches of storage-integrated generation scheduling, the metaheuristics-enabled approach proposed here relieves the modelling complexity of the optimisation, by using fewer decisions variables. Different degrees of solar and wind, as the renewable energy, are penetrated into the system, together with traditional diesel generators. The mixed-coded non-dominated sorting genetic algorithm II (NSGA-II) is employed as the main numeric tool, which shows the advantage of mixed-coded modelling over the real-coded modelling for the generation scheduling problem. The numeric evaluation of the system planning adopts the levelised cost of electricity (LCOE) as the economic indicator, to guide the real system planning and operation.

Keywords: Generation scheduling; Hybrid power system; NSGA-II; Sizing; Stand-alone; Storage dispatch (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (31)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544216310477
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:114:y:2016:i:c:p:671-682

DOI: 10.1016/j.energy.2016.07.123

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().